Instrumental and experiential attitudes toward (A.I.) augmented decision-making at work

Kees Maton, Pascale Le Blanc, Philippe van de Calseyde, Anna-Sophie Ulfert
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Abstract

In augmented decision-making, defined as a process wherein human judgment is complemented with decision-support systems powered by artificial intelligence (A.I.-DSS), employees are expected to monitor and sometimes override system outputs to enhance decision-making performance. Despite the growing use of these costly technologies in organizations, they often fail to add value as employees seem unwilling to delegate some of their tasks to A.I.-DSS or monitor its outputs. Past research has shown that employees differ in their attitudes toward (collaborating with) emerging technologies, and that these attitudes can facilitate or hinder effective technology use. Drawing on literature from technology acceptance (TAM) and user experience (UX), this study qualitatively explored whether employees hold both instrumental (i.e., related to consequences like performance) and experiential (i.e., related to experiences of the process) attitudes toward augmented decision-making, and whether these two types of attitudes differ in terms of their antecedents and outcomes.
Seventeen semi-structured interviews with A.I.-DSS users from various organizations revealed that experiential attitudes were mentioned more frequently, but were significantly less positive than instrumental attitudes. In terms of antecedents, instrumental attitudes were primarily mentioned in relation to technology (A.I.-DSS) characteristics, whereas experiential attitudes were also related to task and individual characteristics. As for outcomes, instrumental attitudes were solely associated with employees’ intentions to use A.I.-DSS, while experiential attitudes were also mentioned in relation to employee absorption, motivation and stress. These findings highlight the importance of distinguishing between instrumental and experiential attitudes toward augmented decision-making at work.
对(人工智能)增强工作决策的工具性和经验性态度
在增强型决策中,被定义为人工智能(ai - dss)驱动的决策支持系统补充人类判断的过程,员工需要监控并有时覆盖系统输出以提高决策绩效。尽管企业越来越多地使用这些昂贵的技术,但它们往往无法增加价值,因为员工似乎不愿意将一些任务委托给人工智能决策支持系统(ai - dss)或监控其产出。过去的研究表明,员工对新兴技术(与之合作)的态度不同,这些态度可以促进或阻碍有效的技术使用。利用技术接受(TAM)和用户体验(UX)的文献,本研究定性地探讨了员工是否对增强决策持有工具性(即与绩效等结果相关)和体体性(即与过程经验相关)态度,以及这两种态度是否在其前因和结果方面有所不同。对来自不同组织的17位人工智能决策支持系统用户进行的半结构化访谈显示,体验态度被提及的频率更高,但其积极程度明显低于工具态度。在前因方面,工具态度主要与技术(人工智能-决策支持系统)特征有关,而经验态度也与任务和个人特征有关。在结果方面,工具性态度仅与员工使用ai - dss的意图相关,而经验态度也与员工吸收、动机和压力有关。这些发现强调了区分工具态度和经验态度对工作中增强决策的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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